Energy-efficient multi-query optimization over large-scale sensor networks

Currently much research work has been done to attempt to efficiently conserve the energy consumption for sensor networks, recently a database approach to programming sensor networks has gained much attention from the sensor network research area. In this paper we developed an optimized multi-query processing paradigm for aggregate queries, we proposed an equivalence class based merging algorithm for in-network merging of partial aggregate values of multi-queries, and an adaptive fusion degree based routing scheme as a cross-layer designing technique. Our optimized multi-query processing paradigm efficiently takes advantage of the work sharing mechanism by sharing common aggregate values among multiple queries to fully reduce the communication cost for sensor networks, thus extending the life time of sensor networks. The experimental evaluation shows that our optimization paradigm can efficiently result in dramatic energy savings, compared to previous work.